2008 Masters and Doctoral Programs
Department of Statistics
George Mason University

The Department of Statistics, George Mason University (website http://statistics.gmu.edu) is accepting applications for its masters and doctoral programs for Fall 2008. The Department also announces the following graduate course offerings in Spring 2008. All graduate courses require 3 semesters of calculus.

Students' Corner

This past October 13, I attended the 3rd Annual Shenandoah Undergraduate Mathematics and Statistics (SUMS) conference, a one-day conference promoting undergraduate research in mathematics, statistics, and their applications. It was held at James Madison University, and featured contributed research talks by undergraduate students, poster sessions with prizes.

There were also invited addresses by Dr. Ann Trenk of Wellesley College and Dr. Michael Krebs of California State University, Los Angeles. Both of these talks were delivered in a lively, informal manner, at a level appropriate for students. Dr. Trenk gave a talk on graph theory, while Dr. Krebs discussed some of the mathematics sudoku puzzles. (Interestingly, Dr. Krebs used some of the graph theory methods that Dr. Trenk had earlier discussed.) If only all technical talks were so fun! And the student presentations were surprisingly sophisticated. It was reassuring to see the students dealing with difficult topics with skill and verve.

I was of course especially interested in the statistical presentations, and I note that out of 28 talks, only four were statistical in nature, the rest being mathematical presentations. Similarly, out of about 32 posters, only about four were about statistics. The conference organizers would very much like to increase the representation of statistical presentations next year. So, if you are an undergraduate student, consider presenting a talk or poster on a statistical topic at next year's SUMS conference. Or, if you teach undergraduate students, please encourage them to attend and perhaps present at SUMS. With free registration, a complimentary lunch, and some travel support, this is an excellent opportunity for undergraduate students to show off their knowledge. If you're interested, I would suggest checking the SUMS website sometime around August 2008, to obtain early information on the conference. The website is: http://www.math.jmu.edu/~brownet/SUMS

If you are eligible to join the society and you are enrolled in a program in the greater Baltimore-Washington metropolitan area, the Washington Statistical Society will cover your initiation fee for the Mu Sigma Rho society. Contact me at jmm97@georgetown.edu for further information.

Earlier this month I received an email from Dr. Dale Atkinson of the Research and Development Division of the National Agricultural Statistics Service in USDA, asking me to circulate a job offer. His group would like to recruit new mathematical statisticians into the agency this year, and in particular are interested in hiring several masters-level people into their Research and Development Division in Fairfax, Virginia. There are also on-going opportunities to start in one of their 45 Field Offices around the country, which is very attractive to some students. You can find the flyer here: http://bist.pbwiki.com/f/Math_Stat_Recruitment_Flyer.pdf

Some of these contacts may be obsolete, but there are many possibilities here. We hope that if you're looking for ideas for internships or jobs, you might mine this extensive list for useful leads.

Last month, I presented B.'s problem, which involved an extension of the Gaussian log-likelihood function to time-series analysis. Yang's solution to B.'s problem can be found here: http://bist.pbwiki.com/f/solution0001.pdf

My friend, Steven J. Fromm of Bethesda, MD, came up with essentially the same solution, and noted that it amounts to completing the square. (Exponents sum when terms are multiplied; the completion of the square is performed on the exponents.)

J.P. is a graduate student in the Interdisciplinary Neuroscience Program at Georgetown University,and recently threw a methods question at me. He is developing an experiment that will examine brain activations associated with keyboard typing, and wants to compare typists of two different skill levels: a high-skill group and a low-skill group. Previous studies have determined that one can discern dissociable performance effects between groups of typists if and only if there is least a 30 word-per-minute (WPM) difference between them, and the standard deviation does not exceed 30 WPM. E.g. one group may have a mean of 55 WPM and the other may have a mean of 85. Note that J.P.'s experimental measurement is not WPM, but brain activity as measured by brain scans. He intends to maximize differences in brain activity between two groups by manipulating the skill levels of the two groups.

So, J.P.'s question is, is there a way to optimally select subjects based on their WPM rate such that after the collection of 32 subjects there are 16 subjects in each group, where there is at least a 30 WPM mean difference between the groups and a maximum of 30 WPM standard deviation within each group? Is it possible to design an algorithm which takes as input the WPM of each subject as they are collected, and then suggests the best WPM for the next subject or set of subjects? For example, after collecting 15 subjects the algorithm might suggest that the next subject or set of subjects collected should have a WPM of 75 or less.

The problem is that the variance of the WPM's of the student population is unknown, at least at the outset. Would it be best to first obtain measurements on 16 subjects, use this as an estimate of the population variance, and then collect the next 16 subjects by weighting towards the upper and lower bounds of the original 16? Or could subject recruitment be performed continuously as data is acquired, use the spread of WPM's acquired thus far to estimate the population variance? From this estimate, perhaps incoming subject selection could be skewed to the highest or lowest 1/3 WPM of the sample acquired thus far.

Or perhaps J.P. should simply ask only people who consider themselves either very good typists or very poor typists to participate.

The problem seems to me to be similar to problems in early clinical trials where one develops algorithms to terminate a study early if too many subjects are experiencing serious adverse effects. Perhaps a Bayesian approach may be applicable, or perhaps a method based on Markov Chains. What do you think?

The latest issue of STATS magazine arrived in my mailbox last week. The cover story is about optimizing a paper helicopter! Let me take this opportunity to again recommend, if you're a student of statistics, that you obtain student membership in the ASA, if you haven't already, if only just to receive this magazine. Join online here: https://www.amstat.org/membership/index.cfm?fuseaction=onlineapp Scroll down to the section entitled "STUDENT". It's only $10!

Also consider student membership in the local chapter of the ASA, the Washington Statistical Society. You can join online at: http://wws.scs.gmu.edu/~wss/join.html.

That's all for this month. If you have any feedback on this column or ideas for future topics, please email me at jmm97@georgetown.edu. Your thoughts will be greatly appreciated.

SIGSTAT Topics for Fall 2007

November 21, 2007: Survival Models in SAS: PROC LIFETEST - Part 2

Continuing the series of talks based on the book "Survival Analysis Using the SAS System: A Practical Guide" by Paul Allison, in November we'll finish Chapter 3: Estimating and Comparing Survival Curves with PROC LIFETEST. Topics discussed are:

Continuing the series of talks based on the book "Survival Analysis Using the SAS System: A Practical Guide" by Paul Allison, in November we'll start Chapter 4: Estimating Parametric Regression Models with PROC LIFEREG. Topics discussed are: